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Computationally efficient sequential learning algorithms for direct link resource-allocating networks by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

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Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal by Camellia , Mohd Kamal

“…For Perception there will be the Description Neuron Model, Perceptron Basic Architecture and perceptron Algorithm with one example of solved problem. …”
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A step towards the development of VHDL model for ANN based EMG signal classifier by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…A feed-forward ANN with back-propagation learning algorithm is used for the classification of EMG signals. …”
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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan by Hamdan, Ezaryf

“…This paper proposes a sophisticated Job Position Prediction system utilizing Machine Learning algorithms and leveraging data from LinkedIn profiles. …”
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Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

“…This research aims include preprocessing lung nodular data, developing the proposed algorithm, and comparing its effectiveness with other methods. …”
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Deep learning framework for hierarchical-based object identification and description by Alamro, Loai C. A.

“…In this study, a new DL framework called Human Identification and Description Framework (HIDF) is developed. The HIDF aims to overcome global generalization, hierarchical and correlation learning limitations by describing an object when it cannot be initially identified. …”
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Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak Yahya, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

“…This research aims include preprocessing lung nodular data, developing the proposed algorithm, and comparing its effectiveness with other methods. …”
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Text to Image Generation Using Machine Learning by Rishab, Tiwari, Chitra, K.

“…In order to solve this issue, we carried out a research work where we concentrated on developing the generative adversarial network (GAN), a deep learning-based architecture. …”
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Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

“…Through a brief description of the descriptive model, the data distribution in a histogram shows that the information extracted can give a clear picture in influencing the results to classify digital economic tax compliance. …”
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Factors and types of error that contributes to the difficulties in solving Mathematical problems among Year 5 pupils in SK Goebilt, Kuching / Hardi Rasidi by Rasidi, Hardi

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Customer mobile behavioral segmentation and analysis in telecom using machine learning by Sharaf Addin, Eman Hussein, Admodisastro, Novia Indriaty, Mohd Ashri, Siti Nur Syahirah, Kamaruddin, Azrina, Chew, Yew Chong

“…Unsupervised machine learning algorithm K-means was used to cluster the data, and these results were analyzed and labeled with labels and descriptions. …”
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Identifying living organisms by using artificial neural networks approach / Raifiza Abdul Rahim by Abdul Rahim, Raifiza

“…Artificial neural network (ANN), which is one of the commonly used machine learning technique, might be preferable to form its own descriptions of genetic concepts. …”
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A Fusion-Based Framework For Explainable Suicide Attempt Prediction by Nordin, Noratikah

“…The proposed work aims to analyse an explainable learning algorithms for predicting suicide attempts, propose an ontology model for semantically representing the classification risk of suicide attempts and propose an explanation generation algorithm by combining predictions from explainable machine learning and ontology models. …”
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Statistics Easy Tool (SET) / Noor Aisyah Idris and Nurdia Azlin Ghazali by Idris, Noor Aisyah, Ghazali, Nurdia Azlin

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Current applications of machine learning in dentistry by Ghazali, Ahmad Badruddin, Reduwan, Nor Hidayah, Ibrahim, Roliana

“…Machine learning (ML), a subset of AI was described as an algorithm with the ability to "learn" by identifying patterns in a large dataset (Rowe, 2019). …”
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Unsupervised place recognition for assistive mobile robots based on local feature descriptions. by Tang, Sai Hong, Ramli, Abdul Rahman, Samsudin, Khairulmizam

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Artificial Intelligence Integration in Mobile Applications: Innovation and Challenges in Supporting Quran Memorization and Review by Khairulnazrin Nasir, Rahim Kamarul Zaman, Ahmad Bazli Ahmad Hilmi, Abdul Hakim Mahadzir, Ahmad Mukhlis bin Mustaffa

Framework development in extracting rules from trained neural network / Shuzlina Abdul Rahman, Azlinah Hj Mohamed and Marina Yusoff by Abdul Rahman, Shuzlina, Mohamed (Hj), Azlinah, Yusoff, Marina

“…In addressing this framework, the criteria of each approaches has been explored and analyzed from eight factors: process extraction, merit, demerit, rule type, type of data, rule quality, processing complexity, and the description of each RE technique. The analysis is derived by excavating literature on RE techniques starting from the year 1993 until 2003 focused on supervised learning algorithm. …”
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

“…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

“…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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